Determining Predictor Importance In Multiple Regression Under Varied Correlational And Distributional Conditions

Authors

Tiffany A. Whittaker, The University of Texas at AustinFollow
Rachel T. Fouladi, University of Texas M.D. Anderson Cancer Center at Houston
Natasha J. Williams, University of Texas at Austin

Abstract

This study examines the performance of eight methods of predictor importance under varied correlational and distributional conditions. The proportion of times a method correctly identified the dominant predictor was recorded. Results indicated that the new methods of importance proposed by Budescu (1993) and Johnson (2000) outperformed commonly used importance methods.

DOI

10.22237/jmasm/1036110360